The impact of patients as trainers on registered nurses’ patient engagement in primary care clinics: a qualitative study
Bibliographic record
Abstract
BACKGROUND: In Canada, primary care is usually the front door to health care for people with health issues. Among these primary care services are primary care clinics (PCC), where the competencies of registered nurses (RNs) are needed. However, nursing practice in PCCs is variable and sometimes suboptimal from one PCC to another. In 2019, the Quebec Ministry of Health and Social Services deployed a practical guide for RNs practicing in PCCs. This guide was intended to support best professional and interprofessional practices and enhance the quality of services offered according to a physical-social vision of care, interprofessional collaboration and partnership with the patient. The Formation de formateurs en première ligne (F2PL) project team developed a train-the-trainer educational intervention to support RNs in assimilating the content of this guide. This educational intervention is uncommon because it includes patients as trainers (PTs). PTs developed and provided andragogic content about patient's experience to enhance patient engagement. OBJECTIVE: To describe the impacts of the educational intervention provided by the PTs in nurses' patient engagement practices in PCCs. METHODS: A descriptive qualitative approach was used to describe in-depth changes in RNs' practices. Individual interviews were conducted with 10 RNs and 3 PTs to explore the changes in RNs' practice and the barriers and facilitators to adopting this new practice. An inductive and deductive thematic analysis was carried out according to a conceptual model of patient engagement (the Montreal Model), and emerging themes were condensed into propositions. To ensure credibility, a peer review was conducted with the F2PL team, which includes a patient co-leader. RESULTS: The educational intervention provided by PTs has impacted RNs' practice in 3 ways: awareness or reminding of general principles, updating commitment to already known principles and enhancing the development of new professional skills. CONCLUSIONS: PTs could effectively support the RNs' motivation to use patient engagement practices in primary care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".